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://www.bioengineering.dtu.dk/research/research-sections/section-for-protein-chemistry-and-enzyme-technology/interfacial-enzymology En’Zync is a visionary research center led by Prof. Daniel Otzen, funded by the Novo Nordisk
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Understanding (Prof. Dr. Martin Weigert) Research areas: Machine Learning, Computer Vision, Image Analysis Tasks: fundamental or applied research in at least one of the following areas: machine learning
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at the Medical Faculty of Heidelberg University, in collaboration with Prof. Dr. Irmela Jeremias, invites applications for a PhD student in Bioinformatics / Computational Biology as part of the CRC1709-funded
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learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms
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PhD Position in Theoretical Algorithms or Graph and Network Visualization - Promotionsstelle (m/w/d)
31.07.2025, Wissenschaftliches Personal The Chair for Efficient Algorithms, led by Prof. Stephen Kobourov, is inviting applications for a fully funded PhD position at the Technical University
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the German Research Foundation (DFG), at the University of Tübingen. The project is led by Principal Investigators Prof. Dr. Michael Franke, Dr. Marlen Fröhlich (both Tübingen) and Prof. Dr. Manuel Bohn
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the goal of obtaining a doctorate. It is based in the newly established Animal Neurophysiology group (Prof. Münch) at the Institute of Animal Physiology, at the Faculty of Biology and Chemistry. The salary
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: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
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Self-funded PhD Opportunities in Plant Growth, Reproduction and Stress Responses School of Biosciences PhD Research Project Self Funded Dr Lisa Smith, Dr Sam Amsbury, Prof Andrew Fleming
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of innovative computational methods using Big Data, Behavioural Science and Machine Learning to understand behaviour through the lens of digital footprint/“smart data” datasets, cutting across sectors ranging